System and method for optimizing energy storage component usage

• US 8,024,082 B2
• Filed: 03/11/2009
• Issued: 09/20/2011
• Est. Priority Date: 03/11/2009
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Yan, Weizhong, Richter, Timothy Gerard
• Primary Examiner(s): Zanelli; Michael J.
• Application Number:
  US12/401,726
• Publication Number:
  US 20100235025A1
• Time in Patent Office: 923 Days
• Field of Search: None
• US Class Current: 701/22
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• CPC Class Codes: B60L 2200/26 Rail vehicles
• CPC Class Codes: B60L 2240/62 Vehicle position
• CPC Class Codes: B60W 10/24 including control of energy storage means
• CPC Class Codes: B60W 10/26 for electrical energy, e.g. batteries or capacitors
• CPC Class Codes: B60W 20/00 Control systems specially adapted for hybrid vehicles hybrid vehicle design, B60K6/00; electric vehicles B60L
• CPC Class Codes: B60W 20/12 using control strategies taking into account route information estimation or calculation of non-directly measurable driving parameters B60W40/00
• CPC Class Codes: B60W 2510/085 Power
• CPC Class Codes: B60W 2510/244 Charge state
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: G07C 5/085 using electronic data carriers
• CPC Class Codes: Y02T 10/64 Electric machine technologies in electromobility
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 Electric charging stations
• CPC Class Codes: Y02T 90/14 Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/167 : Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: Y04S 30/14 : Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing

Abstract

A system for optimizing energy storage component usage in a vehicle comprising one of a hybrid vehicle and an electric vehicle, the vehicle comprising a computer programmed to identify if a vehicle position is associated with link data in a database of historical power usage data, the link data comprising measured historical power usage data for a link of vehicle travel. If the vehicle position is associated with the link data, the computer is programmed to obtain the link data of the link from the database, the link data absent terrain information from the database. The computer is also programmed to determine an expected vehicle power usage of the vehicle based on the obtained link data and optimize the energy storage component usage based on the expected vehicle power usage and based on efficiency and life cycle costs of an energy storage component of the vehicle if the vehicle position is associated with the link data.

Claims

1. A vehicle comprising

one of a hybrid vehicle and an electric vehicle;

an energy storage component; and

a computer programmed to;

identify if a vehicle position is associated with link data in a database of historical power usage data, the link data comprising measured historical power usage data for a link of vehicle travel; and

if the vehicle position is associated with the link data;

obtain the link data of the link from the database, the link data absent terrain information from the database;

determine an expected vehicle power usage of the vehicle based on the obtained link data; and

optimize usage of the energy storage component based on the expected vehicle power usage and based on efficiency and life cycle costs of the energy storage component of the vehicle.

2. The vehicle of claim 1 wherein the computer is further programmed to:

collect vehicle data as the vehicle travels along the link; and

store the collected vehicle data in the database.

3. The vehicle of claim 2 wherein the computer, in being programmed to collect vehicle data, is programmed to collect traction motor power usage based on a measurement interval as the vehicle travels.

4. The vehicle of claim 3 wherein the measurement interval comprises one of time and a vehicle position.

5. The vehicle of claim 3 wherein the computer, in being programmed to collect vehicle data, is further programmed to collect one of an accessory load power usage, a vehicle speed, a latitude and a longitude of the vehicle, a date of data acquisition, and a time of data acquisition.

6. The vehicle of claim 5 wherein the computer, in being programmed to store the collected vehicle data, is programmed to:

segment vehicle data collected from vehicle travel into a plurality of links;

associate a portion of the segmented vehicle data with the link data in the database;

combine the segmented vehicle data with data previously collected and stored for the link if the data previously collected and stored for the link exists; and

add the segmented vehicle data as a new entry into the database if the data previously collected and stored for the link does not exist.

7. The vehicle of claim 6 wherein the computer, in being programmed to segment vehicle data into links, is programmed to define a start node and an end node for the link based on one of nodes defined on a digital map of an interest region, characteristic changes of the collected vehicle data, and intersections of two traveled trajectories.

8. The vehicle of claim 6 wherein the computer, in being programmed to combine the collected vehicle data, is programmed to one of interpolate and average the collected vehicle data with the data previously collected and stored for the link.

9. The vehicle of claim 6 wherein the computer, in being programmed to combine the collected vehicle data, is programmed to combine the collected vehicle data with data previously collected via one of another vehicle and a fleet of other vehicles.

10. The vehicle of claim 1 further comprising:

a vehicle position sensor; and

wherein the computer is further programmed to;

measure the vehicle position via the vehicle position sensor;

measure a direction of travel of the vehicle via the vehicle position sensor; and

identify if the link data in the database are associated with the direction of travel.

11. The vehicle of claim 10 wherein the vehicle position sensor comprises a Global Positioning System (GPS) sensor.

12. The vehicle of claim 1 wherein the computer is further programmed to set a default state of charge of an energy storage component of the vehicle halfway between a maximum charge and a minimum charge of the energy storage component if the vehicle position is not associated with any link data in the database.

13. A method comprising:

determining whether a vehicle position of one of a hybrid vehicle and an electric vehicle is associated with a first link dataset in a database of historical power usage and velocity data, the first link dataset comprising measured power usage and velocity data related to a first link of vehicle travel; and

if the vehicle position is associated with the first link dataset;

querying the database to obtain historical power usage and velocity data from the first link dataset, the queried data free of elevation data for the first link;

calculating an expected power usage for the vehicle based on the queried data; and

optimizing an energy storage component usage for an energy storage component of the vehicle based on the expected power usage and based at least on efficiency and life cycle costs of the energy storage component of the vehicle such that operation of the energy storage component based on the optimized expected power usage achieves a desired usage of the energy storage component.

14. The method of claim 13 further comprising setting a default state of charge of the energy storage component of the vehicle midway between a maximum charge and a minimum charge of the energy storage component if the vehicle position is not associated with the first link dataset.

15. The method of claim 13 further comprising:

determining a time in which the vehicle is expected to reach an end of the first link based on the vehicle position and historical velocity data;

determining whether the time is greater than a time window of travel; and

if the time is less than the time window of travel;

identifying at least one future link extending from an end node of the first link;

querying the database for historical power usage data measured previously for the at least one future link, the historical power usage data free of elevation data for the at least one future link; and

wherein calculating the expected power usage for the vehicle comprises calculating the expected power usage for the vehicle based on the queried historical power usage data related to the first link and to the at least one future link.

16. The method of claim 15 wherein calculating the expected power usage comprises calculating a weighted average of the historical power usage data measured previously for the at least one future link based on a frequency of vehicle travel along the at least one future link.

17. The method of claim 15 further comprising:

measuring the vehicle position and velocity via a navigation system;

measuring a direction of travel of the vehicle; and

wherein determining whether the vehicle position is associated with the first link dataset comprises comparing the first link dataset with the measured vehicle position and with the measured direction of travel.

18. The method of claim 17 wherein measuring the vehicle position comprises measuring the vehicle position via a Global Positioning System (GPS) sensor.

19. A system comprising:

a vehicle;

a power system configured to provide power to drive the vehicle, the power system comprising;

an energy storage component; and

a traction drive coupled to the energy storage component;

a position sensor configured to measure a position of the vehicle;

a database comprising stored vehicle historical power usage data; and

a computer configured to;

determine a correlation between the position of the vehicle and a segment of the vehicle historical power usage data stored in the database; and

if the position and the segment of data are correlated;

obtain the segment of data from the database, the segment of data free of elevation data;

determine an expected vehicle power usage of the vehicle based on the obtained segment of data; and

optimize an energy storage component usage based on the determined expected vehicle power usage and based on efficiency and life cycle costs of the energy storage component, the optimized energy storage component usage comprising target biasing state of charge setpoints for the energy storage component.

20. The system of claim 19 further comprising:

a state of charge sensor coupled to the energy storage component and configured to measure a state of charge of the energy storage component; and

wherein the computer is further configured to;

identify a target biasing state of charge setpoint based on a position of the vehicle;

determine a state of charge of the energy storage component via the sensor; and

operate the power system to move the state of charge of the energy storage component toward the target biasing state of charge setpoint.

21. The system of claim 20 wherein the computer, in being configured to operate the power system is configured to operate the traction drive in one of a traction mode and a regenerative braking mode.